Obesity and Mortality Risk

New Findings From Body Mass Index Trajectories

Hui Zheng; Dmitry Tumin; Zhenchao Qian

Disclosures

Am J Epidemiol. 2013;178(11):1591-1599. 

In This Article

Abstract and Introduction

Abstract

Little research has addressed the heterogeneity and mortality risk in body mass index (BMI) trajectories among older populations. Applying latent class trajectory models to 9,538 adults aged 51 to 77 years from the US Health and Retirement Study (1992–2008), we defined 6 latent BMI trajectories: normal weight downward, normal weight upward, overweight stable, overweight obesity, class I obese upward, and class II/III obese upward. Using survival analysis, we found that people in the overweight stable trajectory had the highest survival rate, followed by those in the overweight obesity, normal weight upward, class I obese upward, normal weight downward, and class II/III obese upward trajectories. The results were robust after controlling for baseline demographic and socioeconomic characteristics, smoking status, limitations in activities of daily living, a wide range of chronic illnesses, and self-rated health. Further analysis suggested that BMI trajectories were more predictive of mortality risk than was static BMI status. Using attributable risk analysis, we found that approximately 7.2% of deaths after 51 years of age among the 1931–1941 birth cohort were due to class I and class II/III obese upward trajectories. This suggests that trajectories of increasing obesity past 51 years of age pose a substantive threat to future gains in life expectancy.

Introduction

The rising prevalence of obesity has emerged as a potential threat to overall life expectancy in the future. The extent of this threat, however, is still uncertain, and estimates of the percentage of total deaths due to obesity vary widely, from 5%[1] to 13%.[2–4] Although these estimates are all based on measuring the mortality consequences of body mass index (BMI) assessed at baseline (i.e., at 1 point in time), other studies have found that a dynamic measure of weight status (weight or BMI change) is more predictive of mortality than is a static measure of weight status (i.e., baseline BMI), especially among older adults.[5,6] We might expect obesity to increase the risk of death more profoundly when it persists over the life course. Therefore, in order to better assess the rising threat of obesity, it is essential to examine the mortality consequences of BMI trajectories.

Prior studies based on dynamic measures have yielded mixed findings about the mortality consequences of weight change.[5–21] Several factors contribute to the mixed findings. First, the association of weight change with mortality depends on baseline BMI status. Weight gain leads to excess death among overweight/obese individuals but lowers the mortality risk among underweight or normal weight people.[8] Second, the association differs by the magnitude of weight change. Modest weight gains are associated with a decreased mortality risk, but excessive weight gains predict an increased mortality risk.[7,13] When both initial weight and the magnitude of change are taken into account, small weight gains (1.0–2.9 BMI units) are not associated with excess mortality risk among 50–70-year-old Americans, regardless of their initial BMI levels, whereas large weight gains (3.0–5.0 units) increase the risk of death only when the initial BMI is greater than 35. Moreover, both small weight losses (1.0–2.9 units) and large weight losses (3.0–5.0 units) are associated with an increase in the risk of death among people who are normal, overweight, or mildly obese at baseline.[22]

Even though they advanced beyond the use of a static measure of baseline BMI, prior studies nevertheless have suffered from several limitations. First, most studies only considered mortality consequences of weight change between 2 time points, either over the short term[22] or the long term.[8] This approach obscures heterogeneity in weight changes that occur after the second time point, as well as weight fluctuations between the 2 time points. Second, although distinguishing between small and large weight changes is important, the specified cutoffs are necessarily arbitrary and may inadequately represent true variation in the magnitude of weight change. Third, when estimating the interaction effect between weight change and BMI on mortality risk, some studies assumed a linear functional effect; that is, they expect the effect of weight gain or weight loss on mortality to be linear across initial BMI status.[22] This functional assumption, however, is arbitrary and may misrepresent the interaction of weight change and initial weight status.

The objectives of the present study were to capture heterogeneity in the entire BMI trajectory after 51 years of age, examine the mortality consequences of this heterogeneity, and calculate the mortality risk attributable to each trajectory using data from the US Health and Retirement Study (HRS). We used a semiparametric group-based trajectory model or the latent class trajectory model[23–26] to capture heterogeneity in weight changes without specifying artificial cutoff points or a strong functional assumption. This strategy can straightforwardly depict how BMI may increase, decrease, or remain stable among various groups with different initial BMI statuses.

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